| time | topic |
|---|---|
| 30 | Determining which plot is the most effective |
| 15 | Representing uncertainty |
| 15 | Managing multivariate data |
| 20 | Mapping spatial data |
| time | topic |
|---|---|
| 30 | Determining which plot is the most effective |
| 15 | Representing uncertainty |
| 15 | Managing multivariate data |
| 20 | Mapping spatial data |
What would be NOT interesting?
Assess the plot design by embedding it among a field of plots made using the same design on null data.
Measure the frequency at which readers identify the data plot.
\[\bar{X} = \frac{1}{n} \sum_{i=1}^n X_i\]
Statistical power is the probability that if the observed statistic is different from a null, that the test will detect it.
Show the lineup of plots to a set of observers, and record the number of detects. The plot design with the more detects has the higher power, higher signal strength.
We need to break you into two groups.
When your group is labelled close your eyes. No peeking!
There are many types of uncertainty. One is, suppose we had a different sample.
Plot
Interactivity allows examining relationships between more than two variables.
Selecting points using a square “brush”, allows you to see where observations lie in the other plots (pairs of variables).
A map is a collection of points, defining polygons.
Special care:
Numerical value of statistic is attached to the respective polygon.
But a problem, especially for Australia is that small geographic, but high population density, areas get lost.
A cartogram expands a geographic are relative to the population in the area.
See more on cartograms here.
And for a hexagon tiling that works better for Australia here.
Learn more about hexagon tiling that works better for Australia here.
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